People with different ancestries inherit different risks and encounter different environmental exposures resulting in different somatic profiles.
Research Presented at the American Association for Cancer Research (AACR) Annual Meeting, held April 8-13, 2022 in New Orleans, Louisiana, demonstrates that a lack of knowledge about ancestry-specific alterations is a major barrier to implementing precision medicine, leading to inequities in genetic testing, targeted treatment, and clinical trial design for cancer patients from the underserved populations. However, a limited number of cancer cases from non-European populations have been sequenced in a research setting, and paired normal samples are often not collected in routine clinical care.
Researchers from Dana-Farber Cancer Institute in Boston, MA, and Foundation Medicine in Cambridge, MA looked at patients with African, South Asian, East Asian, American, and European ancestry from comprehensive genomic profiling (CGP) of over 200,000 tumors and identified 18,717, 8,588, and 6,594 patients with significant proportions of African, American, East Asian ancestry, respectively.
Using logistic regressions with the age of diagnosis, gender, and tumor mutation burden (TMB) as covariates, they identified 165 ancestry-associated genes across 14 common cancer types.
The researchers used reported race and ethnicity data in the American Association for Cancer Research (AACR) project GENIE (Genomics Evidence Neoplasia Information Exchange) cohort for validation. The AACR’s Project GENIE is a publicly accessible international cancer registry of real-world data assembled through data sharing between 19 of the leading cancer centers in the world.
The registry aggregates, harmonizes, and links clinical-grade, next-generation cancer genomic sequencing data with clinical outcomes obtained during routine medical practice from nearly every cancer patient treated at these institutions.
The consortium and its activities are driven by openness, transparency, and inclusion, ensuring that the project output remains accessible to the global cancer research community for the benefit of all patients. AACR Project GENIE fulfills an unmet need in oncology by providing the statistical power necessary to improve clinical decision-making, particularly in the case of rare cancers and rare variants in common cancers, and can power novel clinical and translational research.
Using data collected in project GENIE, the scientists found that endometrial carcinoma patients with African ancestry were enriched with TP53 mutations (OR=2.3, FDR corrected p=5×10-31) but lacked PTEN (OR=0.3, FDR corrected p=2×10-41) and KRAS (OR=0.5, FDR corrected p=8×10-13) mutations.
In colorectal cancer, KRAS (OR=1.5, FDR corrected p=4×10-44) and APC (OR=1.4, FDR corrected p=1×10-16) mutations were enriched in patients with African ancestry, whereas BRAF mutations were depleted in both African (OR=0.5, FDR corrected p=5×10-24) and East Asian (OR=0.6, FDR corrected p=6×10-5) patients.
CDK12 mutations were enriched in both African (OR=1.6, FDR corrected p=2×10-4) and East Asian (OR=3.1, FDR corrected p=2×10-7) prostate cancer patients. For patients with AMR ancestry, increased mutation frequency was observed in SETD2 in pancreatic cancer (OR=3.4, FDR corrected p=1×10-4), and VHL in renal clear cell carcinoma (OR=1.9, FDR corrected p=2×10-4). In GBM, TERT alterations were associated with European ancestry (OR=1.3, FDR corrected p=0.003).
Interestingly, TMB-high status was associated with EUR ancestry in melanoma (OR=5.9, p=6×10-36) and anti-correlated with African ancestry in endometrial carcinoma (OR=0.7, p=1×10-6).
The scientists observed that their large-scale ancestry analysis characterized the somatic landscape of non-European cancer patients. Future directions include quantifying the germline heritability of identified ancestry-associated mutations using a local ancestry risk score (LRS) and investigating ancestral effects on cancer prognosis and outcome using the GENIE cohort.
Carrot-Zhang J, Newberg J, Frampton G, Beroukhim R.Leveraging existing data to identify ancestry-associated features across multiple cancer types.[Abstract]. In: Proceedings of the 113th Annual Meeting of the American Association for Cancer Research; 2022 April 8-13; New Orleans LA. Philadelphia (PA): AACR; 2022. Abstract nr 1166 / 13 [Abstract]
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